Open Access Journal

ISSN : 2456-1304 (Online)

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Open Access Journal

International Journal of Science Engineering and Management (IJSEM)

Monthly Journal for Science Engineering and Management

ISSN : 2456-1304 (Online)

Review on Revolutionizing Blood Cancer Treatment: Integrating AI with Carbon Nanotubes for Drug Delivery

Author : Dipika Gaikwad, Dr. Rupali Sonolikar

Date of Publication :3rd July 2024

Abstract: Advances in nanotechnology and artificial intelligence (AI) have revolutionized cancer research and treatment, including cancer treatment. Carbon nanotubes (CNTs), in particular, have shown great potential in drug delivery due to their unique properties such as high surface area, electrical conductivity, and biocompatibility. This article will discuss the current status, challenges, and future directions of AI-CNT integration in blood cancer research. The purpose of this article is to provide information on a review of routine tools used in hematology research. The purpose of this review is to explore the use of deep learning (DL) and machine learning (ML) in the treatment of blood tumors of all stages and types of hematological malignancies. Our goal is to develop actionable guidelines for further blood cancer research. Analysis; It is the result of database research in top databases, including PubMed, Science Direct, Springer, NCBI, and Elsevier journals. The backlog is carefully reviewed and compiled to create an authoritative and up-to-date version of the field. This article describes the properties of carbon nanotubes, explains their operating methods, and demonstrates their role in cancer diagnosis and treatment. Carbon nanotube-based drug delivery can improve the biodistribution of medical drugs and bind blood circulation, thus improving the effectiveness of the drug and reducing the dosage. Using AI to determine the best treatment for a patient's stage of cancer requires further research, as treatments such as chemotherapy can be problematic and repeatable, requiring risk assessment and mitigation planning. Objective - The aim of this paper is to provide a comprehensive analysis of modern AI techniques used in the field of haematology. In particular, we highlight the use of AI-CNT for targeted drug delivery in hematologic malignancies and the application of AI to determine the best course of treatment based on the patient's cancer stage. Our goal is to explore the application of ML and DL techniques in the study of blood cancers. The purpose of this analysis is to map out possible directions for further blood cancer research. Review method - This review article is the result of database research in top databases, including PubMed, Science Direct, Springer, NCBI, and Elsevier journals. The research focuses on research and literature review on the use of CNT and AI-assisted drug delivery in cancer research, using topics such as blood cancer, artificial intelligence, medicine, nanotechnology, CNT-based drug delivery, AI-assisted drug delivery. The backlog is carefully reviewed and compiled to create an authoritative and up-to-date version of the field. To ensure the best quality selected articles have been checked for publication integrity and accuracy. Conclusion - Current literature indicates that AI applications in hematology have achieved notable success in screening, diagnosis, and treatment. However, there remains a need to optimize patient treatment pathways by predicting malignancy based on symptoms or blood records, an area that has yet to be thoroughly explored

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